About us
Shalion is a data and insights-driven company that serves world-class manufacturers and brands globally. Through our Digital Shelf Optimization, Retail Media, and Food Service Aggregators solutions, we provide innovative tools for e-commerce monitoring.
At Shalion, we empower brands to make smarter business decisions in eCommerce by delivering actionable data and insights on online product prices, availability, share of search, and more. We operate across 1000+ e-retailers in 60+ countries, serving industry giants such as Heineken, Lego, Danone, Nestlé, and JDE.
As a leader in data intelligence, we specialize in gathering, analyzing, and applying proprietary artificial intelligence to deliver relevant data and monitoring tools, helping our clients maximize their e-commerce performance.
The role
As a Machine Learning Engineer, you will join our Data Science team and play a key role in transforming research-driven work into robust, production-ready systems. You will help elevate the team’s engineering maturity, promote best practices, and ensure that models are scalable, maintainable, and deliver real business impact.
Your Responsibilities:
- Own the end-to-end lifecycle of ML systems, with focus on deployment and monitoring
- Refactor and productionize existing models and notebooks into clean, modular, and testable code.
- Introduce and enforce best practices in coding, testing, model versioning
- Set up and improve CI/CD workflows for ML systems
- Work closely with Data Scientists and Data Engineers to ensure clean interfaces and reliable data flows
- Act as a technical reference within the team, reviewing code and guiding less experienced members
Your profile:
- 3+ years of experience building and deploying ML systems in production environments
- Strong software engineering skills in Python, with a focus on writing clean, maintainable, and testable code
- Proven experience taking models from notebook to production
- Solid understanding of model development lifecycle
- (Bonus) Familiarity with containerization (Docker)
- (Bonus) Experience with cloud environments (AWS preferred) and data platforms such as Snowflake
Soft Skills:
- Pragmatic and solution-oriented: you focus on what works in production, not just in theory
- Comfortable working in ambiguous environments and bringing structure where needed
- Quality-driven mindset with attention to maintainability and long-term scalability
Interview process:
- First interview: Intro & mutual fit
- Second interview: Technical discussion
- Third interview: Deep dive with Tech Lead
What we offer you
- An international team – Work with colleagues from 10+ nationalities.
-